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Batch - Jun 2021

200,000.00 Enrol Now

Duration 12


Start - 27th Jun 21
Sundays from 10.00 a.m. to 01.15 p.m. IST

Organizations today operate in a world surrounded by data, and data that is understood and analyzed smartly can play a pivotal role in determining the success of many businesses. Data Science, through its various inherent tools and techniques, is successfully adding value to all the business models by using statistics and deep learning to make better, more relevant and timely decisions. Understanding the dynamics of data and knowing how to deal with it has therefore become a critical skill in an organizational context. No wonder that Harvard Business Review has termed Data Scientist as the Sexiest Job of the 21st Century!

The objective of this course is to introduce participants to the intricacies of data science, and techniques of machine learning. This course will expose participants to hands-on experience of popular and in-demand tools in the BDA and ML area. Furthermore, it has been designed with an intention to impart practical problem solving skills to participants which in turn will enhance prospects of career growth.

Learn from the Eminent Faculty of IIIT

Lectures imparted by eminent faculty from IIIT Allahabad and Subject Matter Experts

Hands-On Development of Programming Skills

Knowledge imparted through walkthrough, demonstrations and class exercises to develop hands-on skills

Work on a Capstone Project

Opportunity to work on a Capstone Project as a part of the program

Practical & Application Oriented Knowledge

Program completely oriented towards imparting practical and application oriented knowledge

Certificate of Completion and Alumni Status of CSTCP-IIITA

On successful completion of the course, earn a Certificate of Completion and gain Alumni Status

1 Month Integrated Internship

Opportunity to complete 1 month of professional Internship doing hands-on projects with TransOrg Analytics

Learn Programming Languages & Tools

Programming languages and tools covered include Python, Scikit Learn, Tensor Flow etc.

2 On-Campus Immersion Modules

Two Campus Immersion modules of 3 days each, at the commencement and culmination of the program, that provides participants with an opportunity to experience the campus, meet the faculty and network with peers

Career Management Services from Right Management

As a participant of this program, avail the following career management services offered across 3 months, exclusively by talent and career management experts from Right Management (a Manpower Group company)

  • Personalized and individual engagement across 3 months
  • Resume development and leveraging LinkedIn for professional branding
  • Interview Preparation
  • Personalized 1 on 1 Mock Interview session
  • Curated Job Search Support
  • Individual Career Coaching
  • Access to the RightEverywhere Portal
Duration 12


Start - 27th Jun 21
Sundays from 10.00 a.m. to 01.15 p.m. IST

200,000.00 Enrol Now

Who should attend


  • For Indian Participants – Graduates (10+2+3) from a recognized university (UGC/AICTE/DEC/AIU/State Government) in any discipline
  • For International Participants – Graduation or equivalent degree from any recognized University or Institution in their respective country
  • Mathematics or Statistics as a subject in Class XII or Graduation
  • Formal education in, or knowledge/experience of any programming language would be beneficial
  • This program is entirely hands-on and so it is recommended, though not a necessity that students have two devices (laptop/desktop) – one to follow the lecture, and the other for hands-on practice alongside, during the class


Dr. Manish Kumar

Programme Co-ordinator
CSTCP-IIIT Allahabad, Prayagraj

Dr. Manish Kumar has completed M.Tech(CS) from BIT Mesra and got Ph.D. degree from Indian institute of information Technology, Allahabad, Prayagraj, India on topic” Data Management in Wireless Sensor Networks. Presently he is working as an Associate Professor in Department of IT, IIIT-Allahabad. He is coordinator of research lab Data Analytics Laboratory (DAL) at IIIT-A. His research interest includes Data aggregation, data processing, inference, Compressive sensing in WSNs & big data analytics.

Prof. Shekhar Verma

Professor (IT)
CSTCP-IIIT Allahabad, Prayagraj

Prof. Shekhar Verma received the Ph.D. degree in computer networks from the Indian Institute of Technology (BHU), Varanasi, India, in 1993. He is currently working as a Professor (IT) with the Indian Institute of Information Technology, Allahabad, India. His research interest includes machine learning, computer networks, wireless sensor networks, wireless networks, information and networks security, vehicular technology, and cryptography.

Prof. T. Lahiri

CSTCP-IIIT Allahabad, Prayagraj

Professor Tapobrata Lahiri has completed his Ph.D. from the University of Kalyani, West Bengal. Presently he is working as a Professor in the Department of Applied Sciences, Indian Institute of Information Technology, Allahabad.
His areas of interest and research include the Application of Numerical Analysis Techniques (Machine Learning, Artificial Intelligence, Optimization, Systems Modelling and Simulation, Fractal Dimensional Analysis) to improve Prediction and Automatic Expert/Diagnostic Models for Biomedical area using data/feature extracted from mainly Digital Image and Signal Processing.

Prof. O. P Vyas

CSTCP-IIIT Allahabad, Prayagraj

Prof. O.P. Vyas has done M.Tech. in “Computer Science & Data Processing” from IIT Kharagpur and Ph.D. in “Congestion Control and QoS provisioning in ATM Networks” under joint collaboration with Technical University of Kaiserslautern (Germany) and IIT Kharagpur. His current research interest includes Linked Open Data Mining, Cyber Security, and Service-Oriented Network Architectures. He teaches Object-Oriented Software Engineering, Business Informatics, Data Mining & Warehousing, and guided 16 Research Scholars for Ph.D.

Dr. Neetesh Purohit

Associate Professor
CSTCP-IIIT Allahabad, Prayagraj

Dr. Neetesh Purohit is an Associate Professor at IIITA Prayagraj. His research and development work in the fields of wireless communications, ICT and DSP has significant involvement of the principles of statistics.

Dr. Bhaskar Biswas

Associate Professor, IIT-BHU, Varanasi

Dr. Bhaskar Biswas is an associate professor in the Department of Computer Sci. & Engineering, Indian Institute of Technology (BHU), Varanasi. He acts as a visiting faculty at IIIT, Allahabad, and teaches C Programming and Data Structures.
His main areas of interest are Data Mining, Web Mining, and Social Network Analysis.

Dr. Satakshi

Assistant Professor, SHUATS Prayagraj

Satakshi received her M.Sc. (1998) and M.Phil (1999) in Mathematics from University of Roorkee. In 2004, she received a Ph.D. in Applied Mathematics from IIT Roorkee and later joined Birla Institute of Technology and Sciences, where she worked as a faculty of Mathematics for two years. In 2017, she joined Sam Higginbottom University of Agriculture, Technology and Sciences, where she is currently working as a faculty in the Department of Mathematics and Statistics. Her research interests include order reduction of linear systems, optimization, Evolutionary Algorithms, Machine Learning, Time Series etc.

Dr. Ashutosh Mishra

Associate Professor
CSTCP-IIIT Allahabad, Prayagraj

Dr. Ashutosh Mishra earned his Ph.D. in Electrical and Computer Engineering from Old Dominion University, Virginia, USA. Currently, he is working as an associate professor of Biomedical Engineering (Dept. of Applied Science) at Indian Institute of Information Technology, Allahabad.

His main areas of interest include Bioelectrics, Learning Machines, Distributed Computation and Biomedical Instrumentation and Signals.

Dr. Pavan Chakraborty

Associate Professor
CSTCP-IIIT Allahabad, Prayagraj

Professor. Dr. Pavan Chakraborty teaches as Head of the IT department at IIIT, Allahabad. He has vast areas of interests that include, Human Gait Analysis, Human Prosthetics, Bio-metrics, Image Processing, Graphics, and Visual Computing, Graphical Projections, Robotics & Instrumentation, Real-Time Simulation, High-Performance Computing (HPC), Artificial Life Simulation and Intelligence, Human-Computer Interaction, Astronomy and Astrophysics, Large Astronomical Data Analysis, Cometary Jets Simulation, etc.

Dr. Krishna Pratap Singh

Associate Professor
CSTCP-IIIT Allahabad, Prayagraj

Dr. Krishna Pratap Singh is an Associate Professor at Department of Information Technology, Indian Institute of Information Technology Allahabad. Prior to this he worked as an Assistant Professor (2013-2018), and Lecture (2009-2012) at IIIT Allahabad. He did PhD & Master from IIT Roorkee in 2009 & 2004 respectively. He is heading Machine Leaning & Optimization Lab at IIITA. His teaching & research interests are Machine learning, representation learning, Transfer Learning & Optimization.

Dr. Venkatesan Subramanian

Associate Professor
CSTCP-IIIT Allahabad, Prayagraj

Dr. Venkatesan Subramanian is an Associate Professor in the Department of Information Technology, Indian Institute of Information Technology Allahabad. He received Ph.D. in 2010 from the Department of Computer Science and Engineering at Anna University, Chennai, India in the area of Mobile Agent Security. He has published more than 20 papers in reputed International Journals and Conferences. His current research interests includes Blockchain technology, Network and Information Security. His teaching interest includes Compiler Design, Computer Networks, Blockchain and Cryptocurrency and Database Security.

Dr. Sonali Agarwal

Associate Professor
CSTCP-IIIT Allahabad, Prayagraj

Prof. Dr. Sonali Agarwal is currently working as an Associate Professor in the Information Technology Department of the Indian Institute of Information Technology (IIIT), Allahabad, India. She earned her Ph. D. Degree at IIIT Allahabad and later joined as a member of faculty, where she has been imparting education to aspiring engineers since October 2009. Her main interests are in the areas of Stream Analytics, Big Data, Stream Data Mining, Complex Event Processing System, Support Vector Machines, and Software Engineering.


Dr. Suneel Yadav

Assistant Professor
CSTCP-IIIT Allahabad, Prayagraj

Suneel Yadav has received a Ph.D. degree in the discipline of Electrical Engineering with the Indian Institute of Technology, Indore, India, in 2016. He is currently working with the Department of Electronics and Communication Engineering, Indian Institute of Information and Technology Allahabad, Prayagraj, India, as an Assistant Professor. He is serving as a faculty in-charge of Mobile and Wireless Networking Laboratory (MoWiNeT) at Indian Institute of Information and Technology Allahabad, Prayagraj, India. He has numerous publications in peer-reviewed journals and conferences. His current research interests include detection and estimation theory, signal processing, wireless relaying techniques, cooperative communications, cognitive relaying networks, device-to-device communications, reconfigurable intelligent surfaces, physical layer security, Internet of Things, and MIMO systems.


Participants, who successfully complete the evaluations and satisfy the requisite attendance criteria, will be awarded a certificate of completion. Participants who are unable to clear the evaluation criteria but have the requisite attendance will be awarded a participation certificate.

Talentedge Way

  • 95 %
    Completion Rate
  • 100 %
    Satisfaction Score
  • 79 %
  • Live & Interactive Digital Learning

    Live tutored classes not recorded sessions

  • Case study learning

    Hands-on learning using case studies, projects and simulations

  • Convenient class schedule

    Scheduled classes at convenient timings for working professionals

  • One on one interactions

    All classes are delivered live by the eminent faculty encouraging interactive discussions and query resolution

  • Mobile platform enabled

    Seamless learning on all screens; desktop, laptop, tabs & mobiles through app and browsers

  • Classroom based learning

    Interactive in session peer to peer and with faculty discussions for in-depth learning against isolated learning of recorded sessions

Duration 12


Start - 27th Jun 21
Sundays from 10.00 a.m. to 01.15 p.m. IST


The delivery would comprise a judicious mix of live virtual lectures, discussions, case studies and experience sharing through peer discussions. The course design is oriented to facilitate learning through association of the various management concepts and its application in the business world. Across different modules, participants may be encouraged to apply or relate their in-class learning to live situations at work. Peer learning therefore, would be a key pillar of the process. Take-home projects may be assigned in certain modules.

All enrolled students will also be provided access to our SLIQ Cloud Campus through which students may access other learning aids, reference materials, assessments, case studies, projects and assignments as appropriate. Throughout the duration of the course, students will have the flexibility to reach out to the professors, real time during the class or offline via our SLIQ Cloud Campus to raise questions and clear doubts.


Evaluation methodology is the discretion of the faculty. The methodology includes module based assessments, class contribution, capstone project and any other component as decided by the respective course faculties. Additionally, faculty may choose to conduct a pre-assessment prior to the commencement of certain modules, to ascertain participant readiness to progress further. Basis analysis of the pre-assessment, an individual participant may be required to undertake some refresher/self-study on certain basic areas to help better cope and comprehend the program content.

A minimum of 75% attendance to the live classes is a prerequisite for the successful completion of this program. The program may require participants to work on individual/group assignments and/or projects. The main objective of such assignments/projects will be to help the participants apply their conceptual learning in the program to actual/real life scenarios.

About Right Management

RightCareerEdge is a personalized career advancement service offered by Right Management, India. Established in 1980, Right Management is a global career expert with 40 years of experience in career management and talent strategy. During this time, Right management has put 40,000 people to work every day, conducted over 12 million interviews per year and successfully transitioned more than three million people into new roles. In today’s competitive world, it is critical to constantly evolve in one’s career by deploying innovative career strategies that help an individual achieve his/her career goals. Right Management’s extensive research suggests that majority of job seekers are unclear about their career aspirations & paths and how to achieve them. Our extensive research also unfolds a set of critical parameters for an individual to achieve high career growth. RightCareerEdge has been specifically curated to support professionals to excel in their careers.


CSTCP-IIIT Allahabad, Prayagraj

Established in 1999 as a center of excellence in Information Technology and allied areas, Institute was conferred the Deemed University status by Govt. of India in the year 2000.

In 2014 the IIIT Act was passed, under which IIITA and four other Institutes of Information Technology funded by the Ministry of Human Resource Development were classed as Institutes of National Importance. Recently, IIITA Prayagraj has instituted the Centre for Short Term Certification Programmes (CSTCP) with the primary aim of conducting online courses through suitable online platforms provided by various companies.

IIIT-Allahabad was ranked 119 in BRICS nation by the QS World University Rankings of 2019. Among government engineering colleges in India, IIIT-Allahabad ranked 10th by India Today in 2019 and 18 by Outlook India in 2019. It was ranked 82 among engineering colleges by the National Institutional Ranking Framework (NIRF) in 2019. IIIT-A is very famous for its placements and coding culture.


  • 0#
    ranked 10th by India Today in 2019
  • 0#
    ranked 119 in BRICS nation by the QS World University Rankings of 2019


Data scientists must know how to code – start by learning the fundamentals of one of the most popular programming languages – Python.

Introduction to Python

A brief introduction to Python and its installation along with different Integrated Development Environments (IDE) that support Python

Python basics

Understanding different variable types and operators in Python

Python data structures

Working with different data structures and their usage such as list, dictionary, and tuple

Python programming

Understanding concepts of control and looping, conditional statements, and functions in Python programming

Use of standard libraries – Working with Python packages which are specifically tailored for certain functions, such as:

NumPy: Also known as Numerical Python mostly used in mathematical operations

Pandas: Package to build data frames used for creating features and processing the data

Matplotlib and Seaborn: Packages used for data visualization in Python

Statsmodel and Scipy: Used for statistical modelling and testing

Scikit-Learn: Used for machine learning and advance analytics algorithms

Once you have the core skill of programming covered– dip your feet in the nitty-gritties of working with data, by learning how to wrangle and visualize them.

Reading CSV, JSON, XML and HTML files using Python

NumPy & Pandas

Relational Databases and Data Manipulation with SQL

Scipy Libraries

Loading, Cleaning, Transforming, Merging, and Reshaping Data

It is impossible to use data without knowledge of mathematics. Collect, organize, analyze, interpret, and present data using these concepts of mathematics specially probability, statistics and linear algebra.


Probability & Statistics

Descriptive Statistics & Data Distributions

Probability Concepts and Set Theory

Probability Mass Functions

Probability Distribution Functions

Cumulative Distribution Functions

Modeling Distributions

Inferential Statistics


Hypothesis Testing

Implementation of Statistical Concepts in Python


Linear Algebra


Eigen Vectors & Eigen Values

Matrix Manipulation


Machines have increased the ability to interpret large volumes of complex data. Combine aspects of computer science with statistics to formulate algorithms that help machines draw insights from structured and unstructured data.

Building Models Using Below Algorithms

Linear and Logistics Regression

Support Vector Machines (SVMs)

Random Forests


Decision Tree, Random Forest, K-Nearest Neighbors

Partition Based & Hierarchical Clustering

Principal Component Analysis

Text Analytics

Complex data sets call for simple representations that are easy to follow. Visualize and communicate key insights derived from data effectively by using tools like Matplotlib.

Interactive Visualizations with Matplotlib

Dashboard Development

Exploratory Visualization

Go beyond superficial analysis of data by learning how to interpret them deeply. Use deep-learning nets to uncover hidden structures in even unlabeled and unstructured data using TensorFlow.

Basics of Neural Network

Linear Algebra

Implementation of Neural Network in Vanilla

Basics of TensorFlow

Convolutional Neural Networks (CNNs)

Recurrent Neural Networks (RNNs)

Generative Models

Semi-supervised Learning using GAN

Seq-to-seq Model

Encoder and Decoder

Lastly, manage your infrastructure with a data engineering platform like Spark so that your efforts can be focused on solving data problems rather than problems of machines.

Revision of Data Mining algorithms

Introduction to Big Data analytics & Spark

RDD’s in Spark, Data Frames & Spark SQL

Spark Streaming, MLib & GraphX

Time Series Forecasting

Predictive analytics

This program includes two on-campus components of 3 days each which will take place at IIIT Allahabad campus. On Campus session 1 is tentatively scheduled towards end of July 2021 and On Campus Session 2 is tentatively scheduled towards end of May 2022. The final confirmed dates for On Campus sessions will be communicated in due course and is subject to Government advisory regarding Covid 19 situation. However, attendance to On Campus Component, when held, will be mandatory for all participants of this course.

Focus on real business use cases

Enhance theoretical understanding with practical work

Learn directly from practicing Data Scientists and subject matter experts (SMEs)

Understand the applicability of AI and ML in a particular industry domain

Fee Schedule

For Indian Residents

INR 2,00,000 + GST

Payment Deadline: 27/06/2021
For International Students

USD: 4000

Payment Deadline: 27/06/2021
Instalment Schedule
1st Instalment 2nd Instalment
1st Instalment
INR 25,000 +
USD 500
Payment Deadline: 27/06/2021
2nd Instalment
INR 175,000 +
USD 3500
Payment Deadline: 22/06/2021
Effective 01 July 2017, the prevailing Service Tax will be replaced by GST at an effective rate of 18% Attractive Financing Options including Interest Free Loans available. Conditions apply

All applications for this course must be made through an Online Application Form.

In case payment is being made online through Credit Card/Debit Card, please ensure that you have the Credit Card/Debit Card with you at the time of filling out the Application Form. If you have opted to pay the Application Fee/Instalments of the Fee though Demand Draft/Pay Orders, then please ensure that the Demand Draft/Pay Orders for the applicable amount is made favoring “Arrina Education Services Private Limited” payable at Mumbai and is sent to the address provided below along with the downloaded copy of your Application Form. Please ensure that you write your Name, Course Name and Contact number at the back of your Demand Draft/Pay Order.

All Demand Draft/Pay Orders along with a downloaded copy of your Application Form must be sent to.

Student Relations Manager,

21, Institutional Area, Sector 32,
Gurgaon 122001, Haryana, INDIA.

The program fee is payable in instalments as per the instalment schedule provided. In the event of late payment of Instalment 1 or any other subsequent Instalments, a Late Fee is leviable as follows.

  • A Late fee of Rs.1000 + Tax will be charged to the Participant, if the instalment is paid within 7 days from the due date published on the instalment schedule.
  • A Late fee of Rs.2500 + Tax will be charged to the Participant, if the instalment is paid between 8 days from the due date to within 14 days from due date as published on the instalment schedule.
  • If the Fee Instalment is not received within 14 days from the due date, then the Participant shall be considered a dropout and a Rejoining Fee of Rs.5000 + tax will be charged to the Participant if the Participant wishes to continue with and complete the program and rejoining can be accommodated as per program guidelines.

Cancellation by the Participant

  • Requests for refund of fees on account of cancellation of enrolment shall be considered only if such requests are received prior to closure of registration or 21 days before date of course commencement whichever is earlier.
  • In event that such valid requests for refund of fees are received, the application money shall be refunded after deducting a penalty of Rs.5000 and applicable taxes for Indian participants & USD 125 for foreign participants.
  • In all other cases, no refund shall be made.
  • A participant may opt for rescheduling to a later batch of the same program / another program of prior to commencement of the program. However, such intimation must be made by the participant at least fifteen days prior to the commencement of the program. The amounts paid by the participant shall be considered as advance payment towards the next batch / alternative program. Further, the participant shall have to pay an administrative charge of Rs.5000 plus applicable taxes (Indian participants) or USD 125 (foreign participants) for facilitating such rescheduling.

Cancellation by the Talentedge & Institute

Talentedge & the Institute, reserves the right to cancel courses at any time owing to reasons like insufficient enrolments, trainer indisposition or force majeure events. In the event that Talentedge or the Institute cancels a scheduled course, the student will receive full fee refund for the same. All refunds will be processed within 30 days of receipt of a valid refund request.

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